Robust Passivity and Passification for a Class of Singularly Perturbed Nonlinear Systems with Time-Varying Delays and Polytopic Uncertainties via Neural Networks

abstract

• This paper investigates the problem of robust passivity and passification for a class of singularly perturbed nonlinear systems (SPNS) with time-varying delays and polytopic uncertainties via neural networks. By constructing a proper functional and the linear matrix inequalities (LMIs) technique, some novel sufficient conditions are derived to make SPNS passive. The allowable perturbation bound - can be determined via certain algebra inequalities, and the proposed controller based on neural network will make SPNS with polytopic uncertainties passive for all (0, - ). Finally, a numerical example is given to illustrate the theoretical results. 2012 Springer Science+Business Media New York.

authors

• Huang, Tingwen

published proceedings

• CIRCUITS SYSTEMS AND SIGNAL PROCESSING

author list (cited authors)

• Wen, S., Zeng, Z., Huang, T., & Bao, G.

citation count

• 7

complete list of authors

• Wen, Shiping||Zeng, Zhigang||Huang, Tingwen||Bao, Gang

publication date

• June 2013

publisher

• Springer Nature  Publisher

published in

• Circuits, Systems and Signal Processing  Journal

keywords

• Neural Network
• Passivity And Passification
• Spns
• Time-varying Delay

Digital Object Identifier (DOI)

• 10.1007/s00034-012-9509-8

start page

• 1113

end page

• 1127

volume

• 32

issue

• 3

URL

• http://dx.doi.org/10.1007/s00034-012-9509-8